Java使用OpenCV实现人脸识别/人眼检测/图片截取/合成/添加水印

素颜马尾好姑娘i 2022-06-07 00:26 234阅读 0赞

官方下载opencv安装文件: http://opencv.org/releases.html，以windows版本为例，下载opencv-3.1.0.exe

安装后，在build目录下 D:\\opencv\\opencv\\build\\java，获取opencv-310.jar，copy至项目opncv目录（需要新建）

同时需要dll文件 与 各识别xml文件，进行不同特征的识别（人脸，侧脸，眼睛等）

dll目录： D:\\opencv\\opencv\\build\\java\\x64\\opencv\_java2413.dll （dll库）

xml目录：D:\\opencv\\opencv\\sources\\data\\haarcascades\\haarcascade\_frontalface\_alt.xml（目录中有各类识别文件）

下面给出图片的各种操作的源码和运行结果，源码中有各个操作的解释，看代码就可以理解，java代码如下

package com.zmx.opencvtest;
    
    
    import org.opencv.core.*;
    import org.opencv.core.Point;
    import org.opencv.imgcodecs.Imgcodecs;
    import org.opencv.imgproc.Imgproc;
    import org.opencv.objdetect.CascadeClassifier;
    
    import javax.imageio.ImageIO;
    import javax.swing.*;
    import java.awt.*;
    import java.awt.image.BufferedImage;
    import java.io.File;
    import java.io.IOException;
    
    
    
    /**
     * Created by Administrator on 2017/8/17.
     */
    public class DetectFaceTest {
    
        static{
            // 载入opencv的库
            String opencvpath = System.getProperty("user.dir") + "\\opencv\\x64\\";
            String opencvDllName = opencvpath + Core.NATIVE_LIBRARY_NAME + ".dll";
            System.load(opencvDllName);
        }
    
    
        /**
         * opencv实现人脸识别
         * @param imagePath
         * @param outFile
         * @throws Exception
         */
        public static void detectFace(String imagePath,  String outFile) throws Exception
        {
    
            System.out.println("Running DetectFace ... ");
            // 从配置文件lbpcascade_frontalface.xml中创建一个人脸识别器，该文件位于opencv安装目录中
            CascadeClassifier faceDetector = new CascadeClassifier(
                    "D:\\opencv\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml");
    
            Mat image = Imgcodecs.imread(imagePath);
    
            // 在图片中检测人脸
            MatOfRect faceDetections = new MatOfRect();
    
            faceDetector.detectMultiScale(image, faceDetections);
    
            System.out.println(String.format("Detected %s faces", faceDetections.toArray().length));
    
            Rect[] rects = faceDetections.toArray();
            if(rects != null && rects.length > 1){
                throw new RuntimeException("超过一个脸");
            }
            // 在每一个识别出来的人脸周围画出一个方框
            Rect rect = rects[0];
    
            Imgproc.rectangle(image, new Point(rect.x-2, rect.y-2),
                              new Point(rect.x + rect.width, rect.y + rect.height),
                              new Scalar(0, 255, 0));
    
            Imgcodecs.imwrite(outFile, image);
            System.out.println(String.format("人脸识别成功，人脸图片文件为： %s", outFile));
    
    
        }
    
    
        /**
         * opencv实现人眼识别
         * @param imagePath
         * @param outFile
         * @throws Exception
         */
        public static void detectEye(String imagePath,  String outFile) throws Exception {
    
    
            CascadeClassifier eyeDetector = new CascadeClassifier(
                    "D:\\opencv\\opencv\\sources\\data\\haarcascades\\haarcascade_eye.xml");
    
            Mat image = Imgcodecs.imread(imagePath);  //读取图片
    
            // 在图片中检测人脸
            MatOfRect faceDetections = new MatOfRect();
    
            eyeDetector.detectMultiScale(image, faceDetections, 2.0,1,1,new Size(20,20),new Size(20,20));
    
            System.out.println(String.format("Detected %s eyes", faceDetections.toArray().length));
            Rect[] rects = faceDetections.toArray();
            if(rects != null && rects.length <2){
                throw new RuntimeException("不是一双眼睛");
            }
            Rect eyea = rects[0];
            Rect eyeb = rects[1];
    
    
            System.out.println("a-中心坐标 " + eyea.x + " and " + eyea.y);
            System.out.println("b-中心坐标 " + eyeb.x + " and " + eyeb.y);
    
            //获取两个人眼的角度
            double dy=(eyeb.y-eyea.y);
            double dx=(eyeb.x-eyea.x);
            double len=Math.sqrt(dx*dx+dy*dy);
            System.out.println("dx is "+dx);
            System.out.println("dy is "+dy);
            System.out.println("len is "+len);
    
            double angle=Math.atan2(Math.abs(dy),Math.abs(dx))*180.0/Math.PI;
            System.out.println("angle is "+angle);
    
            for(Rect rect:faceDetections.toArray()) {
                Imgproc.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x
                        + rect.width, rect.y + rect.height), new Scalar(0, 255, 0));
            }
            Imgcodecs.imwrite(outFile, image);
    
            System.out.println(String.format("人眼识别成功，人眼图片文件为： %s", outFile));
    
        }
    
    
        /**
         * 裁剪图片并重新装换大小
         * @param imagePath
         * @param posX
         * @param posY
         * @param width
         * @param height
         * @param outFile
         */
        public static void imageCut(String imagePath,String outFile, int posX,int posY,int width,int height ){
    
            //原始图像
            Mat image = Imgcodecs.imread(imagePath);
    
            //截取的区域：参数,坐标X,坐标Y,截图宽度,截图长度
            Rect rect = new Rect(posX,posY,width,height);
    
            //两句效果一样
            Mat sub = image.submat(rect);   //Mat sub = new Mat(image,rect);
    
            Mat mat = new Mat();
            Size size = new Size(300, 300);
            Imgproc.resize(sub, mat, size);//将人脸进行截图并保存
    
            Imgcodecs.imwrite(outFile, mat);
            System.out.println(String.format("图片裁切成功，裁切后图片文件为： %s", outFile));
    
        }
    
    
        /**
         *
         * @param imagePath
         * @param outFile
         */
        public static void setAlpha(String imagePath,  String outFile) {
            /**
             * 增加测试项
             * 读取图片，绘制成半透明
             */
            try {
    
                ImageIcon imageIcon = new ImageIcon(imagePath);
    
                BufferedImage bufferedImage = new BufferedImage(imageIcon.getIconWidth(),
                                  imageIcon.getIconHeight(), BufferedImage.TYPE_4BYTE_ABGR);
    
                Graphics2D g2D = (Graphics2D) bufferedImage.getGraphics();
    
                g2D.drawImage(imageIcon.getImage(), 0, 0, imageIcon.getImageObserver());
    
                //循环每一个像素点，改变像素点的Alpha值
                int alpha = 100;
                for (int j1 = bufferedImage.getMinY(); j1 < bufferedImage.getHeight(); j1++) {
                    for (int j2 = bufferedImage.getMinX(); j2 < bufferedImage.getWidth(); j2++) {
                        int rgb = bufferedImage.getRGB(j2, j1);
                        rgb = ( (alpha + 1) << 24) | (rgb & 0x00ffffff);
                        bufferedImage.setRGB(j2, j1, rgb);
                    }
                }
                g2D.drawImage(bufferedImage, 0, 0, imageIcon.getImageObserver());
    
                //生成图片为PNG
                ImageIO.write(bufferedImage, "png",  new File(outFile));
    
                System.out.println(String.format("绘制图片半透明成功，图片文件为： %s", outFile));
    
            }
            catch (Exception e) {
                e.printStackTrace();
            }
    
        }
    
        /**
         * 为图像添加水印
         * @param buffImgFile 底图
         * @param waterImgFile 水印
         * @param outFile 输出图片
         * @param alpha   透明度
         * @throws IOException
         */
        private static void watermark(String buffImgFile,String waterImgFile,String outFile, float alpha) throws IOException {
            // 获取底图
            BufferedImage buffImg = ImageIO.read(new File(buffImgFile));
    
            // 获取层图
            BufferedImage waterImg = ImageIO.read(new File(waterImgFile));
    
            // 创建Graphics2D对象，用在底图对象上绘图
            Graphics2D g2d = buffImg.createGraphics();
    
            int waterImgWidth = waterImg.getWidth();// 获取水印层图的宽度
    
            int waterImgHeight = waterImg.getHeight();// 获取水印层图的高度
    
            // 在图形和图像中实现混合和透明效果
            g2d.setComposite(AlphaComposite.getInstance(AlphaComposite.SRC_ATOP, alpha));
    
            // 绘制
            g2d.drawImage(waterImg, 0, 0, waterImgWidth, waterImgHeight, null);
    
            g2d.dispose();// 释放图形上下文使用的系统资源
    
            //生成图片为PNG
            ImageIO.write(buffImg, "png",  new File(outFile));
    
            System.out.println(String.format("图片添加水印成功，图片文件为： %s", outFile));
        }
    
    
        /**
         * 图片合成
         * @param image1
         * @param image2
         * @param posw
         * @param posh
         * @param outFile
         * @return
         */
        public static void simpleMerge(String image1, String image2, int posw, int posh, String outFile) throws IOException{
    
            // 获取底图
            BufferedImage buffImg1 = ImageIO.read(new File(image1));
    
            // 获取层图
            BufferedImage buffImg2 = ImageIO.read(new File(image2));
    
            //合并两个图像
            int w1 = buffImg1.getWidth();
            int h1 = buffImg1.getHeight();
    
            int w2 = buffImg2.getWidth();
            int h2 = buffImg2.getHeight();
    
            BufferedImage imageSaved = new BufferedImage(w1, h1, BufferedImage.TYPE_INT_ARGB); //创建一个新的内存图像
    
            Graphics2D g2d = imageSaved.createGraphics();
    
            g2d.drawImage(buffImg1, null, 0, 0);  //绘制背景图像
    
            for (int i = 0; i < w2; i++) {
                for (int j = 0; j < h2; j++) {
                    int rgb1 = buffImg1.getRGB(i + posw, j + posh);
                    int rgb2 = buffImg2.getRGB(i, j);
    
                    /*if (rgb1 != rgb2) {
                        rgb2 = rgb1 & rgb2;
                    }*/
                    imageSaved.setRGB(i + posw, j + posh, rgb2); //修改像素值
                }
            }
    
            ImageIO.write(imageSaved, "png", new File(outFile));
    
            System.out.println(String.format("图片合成成功，合成图片文件为： %s", outFile));
    
        }
    
        public static void main(String[] args) throws Exception {
    
            //人脸识别
            detectFace("E:\\person.jpg", "E:\\personFaceDetect.png");
    
            //人眼识别
            detectEye("E:\\person.jpg",  "E:\\personEyeDetect.png");
    
            //图片裁切
            imageCut("E:\\person.jpg","E:\\personCut.png", 50, 50,100,100);
    
            //设置图片为半透明
            setAlpha("E:\\person.jpg", "E:\\personAlpha.png");
    
    
            //为图片添加水印
            watermark("E:\\person.jpg","E:\\ling.jpg","E:\\personWaterMark.png", 0.2f);
    
    
            //图片合成
            simpleMerge("E:\\person.jpg", "E:\\ling.jpg", 45, 50, "E:\\personMerge.png");
    
        }
    }

上述运行的结果如下：

（1）原图： E:\\person.jpg     水印的图片：E:\\ling.jpg

![Center][]      ![Center 1][]

Running DetectFace ...   
Detected 1 faces  
（2）人脸识别成功，人脸图片文件为： E:\\personFaceDetect.png

![Center 2][]  
（3）Detected 4 eyes  
a-中心坐标 93 and 102  
b-中心坐标 59 and 107  
dx is -34.0  
dy is 5.0  
len is 34.36568055487916  
angle is 8.36588612403259  
人眼识别成功，人眼图片文件为： E:\\personEyeDetect.png

![Center 3][]

图片裁切成功，裁切后图片文件为： E:\\personCut.png

![Center 4][]  
绘制图片半透明成功，图片文件为： E:\\personAlpha.png

![Center 5][]  
图片添加水印成功，图片文件为： E:\\personWaterMark.png

![Center 6][]  
图片合成成功，合成图片文件为： E:\\personMerge.png

![Center 7][]

总结一下，opencv检测眼睛的还是有一些瑕疵，但是人脸检测效果还可以，我的测试就是如此，大家可以参考实现自己的代码。

[Center]: https://img-blog.csdn.net/20170930142424161?watermark/2/text/aHR0cDovL2Jsb2cuY3Nkbi5uZXQvem14NzI5NjE4/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70/gravity/Center
[Center 1]: /images/20220607/a8420c51cf14428aad98caa050a32758.png
[Center 2]: /images/20220607/d15e8ec1bcd344588837f0e014b811fc.png
[Center 3]: /images/20220607/8505a27eb8f14fda860aeb411b4e88c1.png
[Center 4]: /images/20220607/2bdced0aebb946ddabfca57fe8f33bf4.png
[Center 5]: /images/20220607/f0c62a38cea4407d8ecfc102073e867e.png
[Center 6]: /images/20220607/621e46bad0b9416ea517542c286ca987.png
[Center 7]: /images/20220607/9c68166bb06a4a69991c9d7c600ad1da.png